Interpret SICK Trispector PNG

import cv2
import numpy as np

img = cv2.imread('combined.png', cv2.IMREAD_GRAYSCALE)
height, width = img.shape

# Determine the actual height of the component images
real_height = height/3

# Extract the top (intensity) part
intensity_img = img[:real_height,...]

# Extract the botton (heightmap) part
# Since this has two values per pixel, also reshape it to have the correct number of rows
heightmap_raw = img[real_height:,...].reshape(real_height,-1)

# The heightmap is 16 bit, two subsequent 8 bit pixels need to be combined
# ABCD -> A+256*B, C+256*D

# Quick but non-portable (needs little-endian architecture)
heightmap_img = heightmap_raw.view(np.uint16)

# Slower but portable
heightmap_a = heightmap_raw[...,::2].astype(np.uint16)
heightmap_b = heightmap_raw[...,1::2].astype(np.uint16)
heightmap_img = heightmap_a + 256 * heightmap_b

# Note: intensity is np.uint8, heightmap is np.uint16

cv2.imwrite('intensity.png', intensity_img)
cv2.imwrite('heightmap.png', heightmap_img) # This is just an example so I can show the image, writing as PNG will convert to 8bit, losing detail